Key Takeaways
Somewhere in your company right now, an analyst is auditing an invoice across four systems. She pulls it up in one, matches it line by line against a purchase order in a second, compares it to a contract in a third, and rekeys the totals into a fourth. Then she emails five people to confirm it’s approved to pay.
Now multiply that by every invoice and every approval in every middle- and back-office process that runs daily, weekly, and monthly. That is how much of your business still runs on people moving data by hand.
The systems of record holding that data were never built to execute a process end to end, so people become the glue between them. It’s slow, expensive, and opaque.
That is what Agentforce Operations, powered by Regrello, was built to fix. It turns human-first processes into AI-first operations, so small teams can run the work that used to need large ones.
Salesforce spent 25 years reinventing how companies sell, market, and serve. The middle and back office never got that treatment. It’s next.
What the manual work costs
In hundreds of conversations with operations leaders, I’ve seen how much these manual, human-first processes cost.
Speed. A deal closes and then sits, waiting on contract, credit check, and provisioning. The customer is ready to buy and you still can’t invoice.
Leakage. Manual review means sampled review. Duplicate payments and unbilled services don’t hide in the lines somebody checked. They hide in the lines nobody had time to open.
Cost. Every new order and every exception adds work only a person can do, so the back office grows as fast as the front. There’s no leverage in that.
Risk. A control is only as good as the person executing it at 6pm on the last day of the quarter.
Underneath all four, nobody can see the process end to end. Leaders don’t lack the will to fix this. They lack a way to run work across several systems without a person carrying it between them.
Both of the usual fixes cost you something
Hand the problem to an army of consultants and wait out a multi-year transformation. It arrives late, it arrives as custom code somebody else wrote, and your team never learns how it works.
Or build agents on a general-purpose model. They demo well. Then you look at a payment run and realize you can’t put probabilistic output in front of an auditor.
What Agentforce Operations is
Agentforce Operations removes that choice. It has three parts.
An orchestration engine. Built for how operations actually run: processes that last weeks, handoffs between departments and suppliers, exceptions, approvals, deadlines. Not a chat window sitting on top of your data. A process that holds its state for as long as the work takes and always knows what it’s waiting on.
Agents that do the work. Marshall, the super agent, designs the process and then runs it. Inside each step, the specialized back-office agents he assigns read, check, and reconcile the work that used to require a person’s eyes on the screen.
A platform your auditors will accept. It runs on the Agentforce trust layer on Hyperforce, with a full audit trail, and the steps that must run the same way every time run deterministically rather than probabilistically.
The front office already had its reinvention, and Salesforce built much of it. The data those 25 years produced, the order, the contract, the quote, the case, is exactly where back-office work begins. Today that handoff is where work dies. A closed deal waits on a credit check. A signed contract waits on provisioning. An approved invoice waits in somebody’s inbox. Agentforce Operations picks the work up at that boundary and carries it to completion, on the same platform, under the same governance.
Marshall, the super agent
Most AI agents answer questions. Marshall runs your operations.
Marshall is the super agent behind Agentforce Operations, built specifically for supply chain and finance operations. You describe what you need in conversation with Marshall. He asks for clarification, and then he builds the whole thing: the steps and the sequence, the forms people fill in, and the connections into your systems of record. Minutes, not months. No code, no consultants.
What matters most is what he puts inside each step. Marshall has a team of specialized back-office agents that he builds into the process. Read this contract. Check these invoice lines against the purchase order. Reconcile what doesn’t agree. Create the supplier record. Each agent then does that job on its own, without a person queueing the work or walking it through.
And it does the job the same way every time. Marshall configures each agent against your rules and compiles it into a fixed, approved path, so the same input produces the same result and every step is defined before it runs. That is the answer to the payment run problem above. You can trust agents with work an auditor will scrutinize later, because nothing about how it ran was improvised.
Then Marshall orchestrates the process that connects those agents. He routes each item to the right person, chases the ones that stall, escalates what breaches, and keeps every item’s status visible while he does it. Nobody emails five people to find out where something is.
That is the difference between an agent you ask and a super agent you hand the process to.
So one process now carries three kinds of work. System actions and controls execute deterministically. The specialized agents run the same way, within the bounds Marshall set for them. And people keep the judgment calls that should stay with people.
And it runs in Slack, Teams, and email, where your team already works. A request can start in Slack, move through every system it needs to touch, and land an approval in Teams with a full audit trail behind it. The analyst from the opening doesn’t get one more system to log into. She gets four fewer.
The integration tax, and how we stopped paying it
One thing has restricted the true potential of automated operations in almost every company: integration. Reaching into the core systems where the data lives is the tax on every process, and the usual tools are too slow, too expensive, or too brittle to trust in production.
So we asked a different question. What if you didn’t need traditional integration at all?
Systems Integration Agent works on any browser-based application, including the customized SAP, Oracle, and homegrown systems. It learns an application the way a new employee would, by working through it in a secure copy of your environment.
It learns fast. In about 90 minutes it maps how an application works: the fields, the branches, the rules that apply to your business. Then it compiles what it learned into a fixed, approved workflow. It learns your process once and runs it the same way every time. That is what makes the output reliable enough for core operations and auditable enough to prove each step ran exactly as approved.
Take supplier onboarding. Systems Integration Agent reads a new supplier’s details from one system, applies your rules for required fields and country-specific requirements, creates the record in your procurement platform, and returns the new supplier ID when it finishes. The same approach handles invoice processing, data entry, and regulatory reporting, the high-volume work that has always needed a person to move data between screens.
When a screen or layout changes, the agent recognizes what moved, relearns that part on its own, and carries on, typically in about 20 minutes, with the repair logged for an administrator to review. We call it self-healing. The work keeps running and a person stays in control of what changed.
You can’t redesign what you can’t see
Turning a human-first process into an AI-first one takes more than dropping in a few agents. Most processes are shaped around human limits. Work gets batched because a person runs the batch on Fridays. Approvals stack up because nobody trusted the last system. Take the bottleneck out and the design should change with it.
Intelligent Process Optimization, powered by Apromore, reads how your work actually runs from the data your systems already produce. No workshops, no interviews, no consultants reconstructing the process from memory. It shows you where work stalls and where it drifts off the path it’s meant to follow. Then it tells you what to change and what the change is worth, before you build anything. Once your agents are live it keeps measuring them against that baseline, so “is this working” has an answer instead of an opinion.
Proof: Flex orchestrates end-to-end operations with Agentforce
Flex, a global manufacturing and supply chain company with operations across more than 30 locations, runs Agentforce Operations across core operations including work order approvals and third-party risk assessment — work that used to require manual intervention.
More than 95% of Flex’s work order approvals now run automatically. A separate third-party risk assessment process automates roughly 70% of its activities.
“What excites us most about Agentforce Operations is that it goes beyond automating individual tasks,” said John Lane, VP of IT at Flex. “It orchestrates end-to-end workflows across our core systems, enabling teams to focus their expertise where it adds the most value.”
Get started with Agentforce Operations
All you need is a couple of processes to start. POCs are so old school. A one-day session is all it takes to prove beyond any reasonable doubt that you and Marshall can build your process. By the end of that day you’ll know whether it’s worth going further.
From there, you go straight to a multi-week proof of value. The process live, integrated into your systems, and the results measured against the baseline you started from: cycle time, share of work automated, leakage recovered, hours returned to your team. Your numbers on your operations, not a reference story from somebody else’s. It’s a bit of a break from the past, but one we’re pretty sure you’ll love.
To see it in action, connect with your Salesforce account team to schedule a demo.
